The invention relates to the control and maintenance of Cellular Networks. The invention particularly relates to providing a model for controlling the capacity of a cellular network.
For efficient management of cellular networks, several hundreds of parameters and the control of the parameter characteristics are needed. One of the reasons for problems in network control is lack of direct response, because the capacity of an entire cellular network is measured on the basis of about two thousand separate pieces of measurement data. Hence, effective cellular network control would require the monitoring of the impact of hundreds (about 300, for example) of parameters in hundreds (about 500, for example) of measurement results. In addition, the joint impact of the different parameters in the separate measurement results should be monitored, the level of difficulty of the task being comparable to a collective interpretation of a correlation matrix of about 300xc3x97500, for example. In other words, to change one cellular network parameter it would be necessary to always know which measurement results the change will affect and how much. Similarly, for obtaining a particular change in the measurement results, the, most important parameters for the change and their interdependence should be known.
Therefore problems related to network control may become too many and the demands they set may exceed human resources. Parameter changes and the information provided by the separate measurement results are therefore difficult to utilize when more effective means are searched for to manage the problems involved. Data measuring the network capacity is so abundantly available that solutions based on the data cannot made. A cellular network is complex and the data is spread into several applications. This is why there is a need for simple, effective solutions that take all cellular network systems into consideration as a whole.
An object of the invention is therefore to provide a method allowing the above problems to be solved. This is achieved with a method for calculating a model to be used for controlling cellular network capacity and for facilitating the control of the capacity, the method comprising the generating of variable groups from cellular network variables and the determining of the interdependencies of the variable groups of the cellular network. The method is characterized by searching the variable groups for linear combinations dependent on each other, the dependence between the linear combinations and the strength of the dependence being measured by applying a canonical correlation coefficient, and by expressing a multidimensional dependence of two variable groups in pairs by using only a few canonical variable pairs.
The invention also relates to a system for calculating a model to be used for controlling the capacity of a cellular network and for facilitating the control of the capacity, the system being arranged to generate variable groups from cellular network variables and to determine interdependence of the variable groups of the cellular network. The system is characterized in that the system is arranged to search the variable groups for linear combinations dependent one each other, to measure the dependence between the linear combinations and the strength of the dependence by applying a canonical correlation coefficient, a multidimensional dependence of two variable groups in pairs being expressed in the system by using only a few canonical variable pairs.
The preferred embodiments of the invention are disclosed in the dependent claims.
The invention is based on using canonical correlation analysis to reduce the number of problems involved by expressing the interdependencies of two or more variable groups in a concise manner by using canonical variables as strongly dependent on each other as possible. Coefficients related to canonical variables can be utilized, for example, for determining the most important parameters and measurement results in interdependent variable groups.
The method and system of the invention provide several advantages. A canonical correlation analysis helps in the modelling of dependencies between large variable groups and in the determining of the most important variables. The method of analysis of the invention provides a clear solution for the utilization of the vast amounts of data in the cellular network. The method is particularly useful for those wishing to learn something about the interdependencies of parameters and about how the dependencies are connected to the capacity of the cellular network.